activity
20022025
most citedGlobally Optimal Symbolic Regression

14 citations · 14 across the 6 of their papers we have counts for

collaborators

6 papers

math.OC2025

A hybrid combinatorial-continuous strategy for solving molecular distance geometry problems

Leonardo D. Secchin, Wagner da Rocha, Mariana da Rosa +2

The Molecular Distance Geometry Problem (MDGP) is essential to structural biology, as it seeks to determine three-dimensional protein structures from partial interatomic distances.…

q-bio.BM2025

An Angle-Based Algorithmic Framework for the Interval Discretizable Distance Geometry Problem

Wagner da Rocha, Wagner A. A. da Rocha, Carlile Lavor +4

Distance Geometry is central to protein structure determination from Nuclear Magnetic Resonance data, where distance restraints are naturally uncertain. We study the interval Discr…

math.OC2024

Distance geometry with and without the graph

Leo Liberti, Carlile Lavor

We survey theoretical, algorithmic, and computational results at the intersection of distance geometry problems and mathematical programming, both with and without adjacencies as p…

cs.CG2021

An impossible utopia in distance geometry

Germano Abud, Jorge Alencar, Carlile Lavor +2

The Distance Geometry Problem asks for a realization of a given weighted graph in . Two variants of this problem, both originating from protein conformation, are base…

stat.ML2017★ 14 cited

Globally Optimal Symbolic Regression

Vernon Austel, Sanjeeb Dash, Oktay Gunluk +4

In this study we introduce a new technique for symbolic regression that guarantees global optimality. This is achieved by formulating a mixed integer non-linear program (MINLP) who…

math.GM2002

On a Linear Property of Bilinearly Defined Sets in

Leo Liberti

Certain types of bilinearly defined sets in exhibit a higher degree of linearity than what is apparent by inspection.